Georgia Tech Gesture Toolkit

Bluetooth Accelerometer

GT2K Home

Overview

Gesture recognition is becoming a more common interaction tool in
the fields of ubiquitous and wearable computing. Designing a system
to perform gesture recognition, however, can be a cumbersome task.
Hidden Markov models (HMMs), a pattern recognition technique commonly
used in speech recognition, can be used for recognizing certain
classes of gestures. Existing HMM toolkits for speech recognition can
be adapted to perform gesture recognition, but doing so requires
significant knowledge of the speech recognition literature and its
relation to gesture recognition. Thus, we introduce the Georgia Tech
Gesture Toolkit (GT2k), which leverages Cambridge
University's speech recognition toolkit, HTK, to provide tools that
support gesture recognition research. GT2k provides
capabilities for training models and allows for both real-time and
off-line recognition.

Recent Changes

May 15, 2006: Announcing the BETA Release of version 2
GT2K has been rewritten as a Java based toolkit for application
development. You can download a Beta copy now. Download V2
Register
for the Beta (separate from v1 registration)